Project Grant 2550498
- This National Science Foundation (NSF) CAREER project award under CFDA 47.041 (Engineering) aims to advance the autonomy of power grids by developing fundamental theory and strategies to enhance decision speed, resilience, and societal/sustainability awareness of distributed grid management models and algorithms. The $500,000 award, effective from March 1, 2025 to February 28, 2030, supports the University of Texas at Austin in addressing three critical research questions: leveraging agent...
- The National Science Foundation (NSF) awarded a $350,000 Project Grant to Northeastern University under the Engineering program (CFDA 47.041) to develop a robust and efficient state estimator that can trace the fast dynamics of inverter-based renewable energy sources. The project aims to enable effective control feedback signals and facilitate the integration of these renewable sources into power grids, resulting in cleaner, less costly, and more reliable energy delivery. Key aspects of the...
- This five-year, $500,000 National Science Foundation project grant will support research at Arizona State University to develop innovative solutions for time-synchronized estimation in power systems. Funded through NSF's Engineering program (CFDA 47.041), this CAREER award reflects the agency's mission to advance fundamental engineering research and education. The grantee will create new mathematical techniques in convex programming, interval-theoretic learning, and distributed optimization to...
- This National Science Foundation (NSF) Faculty Early Career Development (CAREER) Program grant, under CFDA 47.041 Engineering, aims to develop energy engineering solutions that incorporate the preferences and needs of diverse residential electricity consumers. The $500,000 award to Arizona State University, received on Aug 1, 2024, will fund research to enable the co-management of utility-owned and customer-owned distributed energy assets using artificial intelligence algorithms. The project...
- The National Science Foundation (NSF) awarded a $484,965 project grant under the Engineering (CFDA 47.041) program to New York University (NYU) to develop transformative concepts and methodologies to enhance situational awareness of electric power distribution systems. The project aims to address challenges in integrating distributed renewable energy generation by enabling real-time tracking of distribution system operating states. Key objectives include learning-based continuous-time system...
- The National Science Foundation (NSF) awarded a $145,871 Project Grant under the NSF Engineering program (CFDA 47.041) to the Regents of the University of California at Riverside (UC Riverside) to develop novel data-driven control methods for the safe and secure operation of grid-edge resources (GERs) in modern power systems. The research aims to address the challenges and opportunities presented by the rapid proliferation of distributed energy resources, such as renewable generators, smart...
- This $295,149 Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to address protection challenges arising from the increasing penetration of renewable energy in modern electric grids. The University of Denver is the prime recipient, and the project will run from August 1, 2024 to July 31, 2027. The project will explore novel model-driven and data-driven solutions to ensure dependable fault detection and secure relay operation for power grids...
- This $350,000 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop a new reduced-order dynamic modeling paradigm for accurately representing the impacts of massive distributed energy resource (DER) integration in carbon-neutral power systems. The project, awarded to Arizona State University, will leverage tools in dynamic systems, nonlinear system identification, and machine learning to create physics-based and machine...
- This $150,000 project grant awarded by the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) to Iowa State University aims to develop novel dynamic grid optimization algorithms and modeling tools to effectively accommodate high penetration of renewable energy and ensure reliable power grid operation. The project will focus on addressing key challenges posed by the uncertainty of renewable energy resources and the stability concerns of power grids with high...
- This $500,000 National Science Foundation (NSF) CAREER award, under the Engineering program (CFDA 47.041), aims to improve the computational efficiency of economics-driven transmission planning for electric power systems by up to three orders of magnitude. The project, awarded to the University of Missouri System's Missouri University of Science & Technology, will develop a multi-faceted framework that integrates innovations in modeling, simulation, computing, and design to transform lengthy...
This National Science Foundation (NSF) CAREER grant (CFDA 47.041 - Engineering) awarded to Trustees of Dartmouth College provides $397,111 in funding from September 1, 2025 through January 31, 2030. The project aims to enhance electric power grid operators' situational awareness, improve dynamic model quality, and enable online controls to ensure secure power system operation with high penetration of inverter-based resources (IBRs) such as solar, wind, and battery energy storage. The research will develop transformative theories, algorithms, and applications for dynamic state estimation, model deficiency diagnosis and calibration, and measurement configuration to improve power system reliability and security in IBR-dominated grids. Key innovative elements include a generalized observability theory, integration of Bayesian inference with robust estimation, and a scalable Bayesian framework for parameter estimation and uncertainty quantification. The project will also promote industry-academia collaboration, curriculum development, and training to equip diverse students with experiences in renewable energy and power engineering.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $397.1k | 9/12/25 |